A tutorial on spectral clustering
نویسندگان
چکیده
منابع مشابه
A Tutorial on Spectral Clustering
In recent years, spectral clustering has become one of the most popular modern clustering algorithms. It is simple to implement, can be solved efficiently by standard linear algebra software, and very often outperforms traditional clustering algorithms such as the k-means algorithm. On the first glance spectral clustering appears slightly mysterious, and it is not obvious to see why it works at...
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Spectral clustering is a family of methods to find K clusters using the eigenvectors of a matrix. Typically, this matrix is derived from a set of pairwise similarities Sij between the points to be clustered. This task is called similarity based clustering, graph clustering, or clustering of diadic data. One remarkable advantage of spectral clustering is its ability to cluster “points” which are...
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Spectral clustering is a modern and wellknown method for performing data cluster-ing. However, it depends on the availabilityof a similarity matrix, which in many appli-cations can be non-trivial to obtain. In thispaper, we focus on the problem of perform-ing spectral clustering under a budget con-straint, where there is a limit on the numberof entries which can ...
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ژورنال
عنوان ژورنال: Statistics and Computing
سال: 2007
ISSN: 0960-3174,1573-1375
DOI: 10.1007/s11222-007-9033-z